Oracle Enterprise Data Quality (EDQ) vs SAP Data Quality Management comparison

Oracle and SAP are both solutions in the Data Quality category. Oracle is ranked #16, while SAP is ranked #9 with an average rating of 7.0. Oracle holds a 2.3% mindshare in DQ, compared to SAP’s 3.1% mindshare. Additionally, 88% of Oracle users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.

Oracle Enterprise Data Qual...

Read 8 Oracle Enterprise Data Quality (EDQ) reviews

455 Views
450 Comparison Views

88% willing to recommend

SAP Data Quality Management

Read 3 SAP Data Quality Management reviews

547 Views
520 Comparison Views

100% willing to recommend

Oracle Enterprise Data Qual...

SAP Data Quality Management

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 11, 2025

Oracle Enterprise Data Quality and SAP Data Quality Management compete in data quality management. SAP Data Quality Management holds an advantage with more comprehensive offerings.

Features: Oracle EDQ has capabilities in data cleansing, profiling, and matching, making it suitable for data accuracy. SAP Data Quality Management offers deeper integration with SAP applications, providing real-time data validation and enrichment.

Ease of Deployment and Customer Service: Oracle EDQ is recognized for straightforward deployment and flexible options with strong support. SAP Data Quality Management offers integrated deployment with SAP, benefiting from extensive support and resources.

Pricing and ROI: Oracle EDQ presents a cost-effective solution with a lower initial setup cost, delivering good ROI for dependable data quality needs. SAP Data Quality Management, while higher in initial cost, offers significant ROI through advanced integration and automation.

To learn more, read our detailed Oracle Enterprise Data Quality (EDQ) vs. SAP Data Quality Management Report (Updated: December 2025).

Buyer's Guide

Oracle Enterprise Data Quality (EDQ) vs. SAP Data Quality Management

December 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Oracle Enterprise Data Qual...

Ranking in Data Quality

16th

Average Rating

8.4

Reviews Sentiment

7.9

Number of Reviews

Ranking in other categories

No ranking in other categories

SAP Data Quality Management

Ranking in Data Quality

9th

Average Rating

8.0

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of December 2025, in the Data Quality category, the mindshare of Oracle Enterprise Data Quality (EDQ) is 2.3%, up from 1.4% compared to the previous year. The mindshare of SAP Data Quality Management is 3.1%, down from 4.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality Market Share Distribution
Product	Market Share (%)
SAP Data Quality Management	3.1%
Oracle Enterprise Data Quality (EDQ)	2.3%
Other	94.6%

Data Quality

Featured Reviews

Venkatraman Bhat

Deliver Head - Database and Infrastructure Cloud Services at Tech Mahindra Limited

Fast, has good extraction, validation, and transformation features, and provides good support

Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution.

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VenkatB

Director at Norderia

Embrace efficient data management with integrated features but anticipate some enhancement needs

This tool itself is new. SAP Data Quality Management was brought in by SAP recently, maybe a year or two years back. We just started implementing and we still have not heard exact feedback from the client. It would not be correct if I give feedback now because I don't have accurate feedback from client usage. I feel it is a good tool with some limitations. We compared it with Celonis, which is also one of the other tools in the market. I am more into SAP and S4 HANA, so I am not familiar with all the best tools available in Data Quality Management which can be compatible with SAP. We know there are issues with SAP Data Quality Management. The advantage of this tool that SAP brought is that it is already in-built. You don't need to build another application layer on top of the existing one. The compatibility and response time for these applications within the same database is faster.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Once it is set up, it is easy to use and maintain."

"The features I like most about Oracle Data Quality include extraction, transformation, and validation, which makes it a multipurpose product such as Oracle GoldenGate and Oracle Data Integrator. I also like that Oracle Data Quality is very fast, so you can use it for a large volume of data within a short period. You have to do the validation very quickly, so the solution helps in that area of data quality. Another feature of Oracle Data Quality that I like is the MDM (Master Data Management) where you'll have a single source of protection, and this makes the solution perfect and helpful to my company."

"I have found the most valuable features to be data cleansing and deduplication."

"With Oracle Data Quality, the most valuable feature is entity matching."

"Scalability is good."

"We work with API standards or norms for internal applications, so it's essential for SSE to have tests and pass those tests according to the criteria, which makes SAP Data Quality Management very important for our products."

"Our primary use case is for us to inspect the results from the product and material, and for releasing or leaving the status of the product."

Cons

"If the length of time required for deployment was reduced then it would be very helpful."

"Oracle Data Quality should integrate with data warehousing solutions such as Azure and CWS Office. For example, having the ability to integrate with tools, such as Azure Synapse and SQL data warehousing would be a great benefit."

"Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution."

"Oracle is currently not that intuitive. We need to use programmers to write code for a lot of the procedures. We need to have them write CL SQL code and write a CL script."

"SAP Data Quality Management would be better if it directly integrates with the ME system. Right now, the company has a lot of machines on the shop floor working as a standalone, so you have to use all methods to ensure that the data interface appears on the ME system and that SAP Data Quality Management records the QM results. It would be much easier if the ME system could be integrated directly with SAP Data Quality Management."

"There are some limitations. They are not covering complete scenarios for all the modules."

"I would like for them to develop a feature to able to record all of our inspections; so all the data can go through SAP. It's not user-friendly or easy to get further analysis, so we mostly skip this step."

Pricing and Cost Advice

"The vendor needs to revisit their pricing strategy."

"The price of this solution is comparable to other similar solutions."

Information not available

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Top Industries

By visitors reading reviews

No data available

Manufacturing Company

17%

Computer Software Company

Healthcare Company

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Midsize Enterprise	2
Large Enterprise	7

No data available

Questions from the Community

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What needs improvement with SAP Data Quality Management?

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What is your primary use case for SAP Data Quality Management?

Currently, one of our clients is seeking SAP Data Quality Management solutions, so we are exploring options in that area. The product is not mature yet, so they need to work to improve it. We are a...

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What advice do you have for others considering SAP Data Quality Management?

For smaller organizations, I don't think this much is required. If it is a bigger size client from a business point of view, I definitely recommend this tool. They can use it if they are already us...

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Comparisons

Informatica Intelligent Data Management Cloud (IDMC) vs Oracle Enterprise Data Quality (EDQ)

Compared 51% of the time

Trillium Quality vs Oracle Enterprise Data Quality (EDQ)

Compared 32% of the time

SAP Information Steward vs Oracle Enterprise Data Quality (EDQ)

Compared 17% of the time

More Oracle Enterprise Data Quality (EDQ) Competitors

Informatica Intelligent Data Management Cloud (IDMC) vs SAP Data Quality Management

Compared 24% of the time

SAP Data Services vs SAP Data Quality Management

Compared 16% of the time

SAP Information Steward vs SAP Data Quality Management

Compared 16% of the time

Datactics Data Quality Manager vs SAP Data Quality Management

Compared 12% of the time

Ataccama ONE Platform vs SAP Data Quality Management

Compared 9% of the time

More SAP Data Quality Management Competitors

Product Reports

Buyer's Guide

Data Quality

December 2025

Oracle Enterprise Data Quality (EDQ) report

Download Oracle Enterprise Data Quality (EDQ) product report

Buyer's Guide

Data Quality

December 2025

Download SAP Data Quality Management product report

Also Known As

Datanomic

SAP BusinessObjects Data Quality Management, BusinessObjects Data Quality Management

Overview

Oracle Enterprise Data Quality is a comprehensive tool for improving data integrity through address verification, profiling, cleansing, and synchronization.

Oracle Enterprise Data Quality empowers organizations to manage their data by ensuring integrity and consistency. It provides efficient address verification, data profiling, cleansing, and synchronization. With capabilities like entity matching, deduplication, extraction, transformation, and validation, it supports diverse data types to enhance data quality processes. While it is seamless in data matching and third-party app integration, the platform benefits organizations by supporting Master Data Management for consolidated data protection. However, improvements in documentation, ERP and warehouse integration, cloud and mobile support, and reduced deployment time could enhance the user experience. Pricing strategy and installation challenges, especially involving coding, need attention for broader accessibility.

What are the main features of Oracle Enterprise Data Quality?

Address Verification: Ensures accuracy in address data.
Data Profiling: Analyzes data characteristics for better insights.
Cleansing: Refines data by removing inaccuracies.
Data Synchronization: Aligns data across platforms effortlessly.
Entity Matching: Identifies and matches related entities.
Deduplication: Eliminates redundant data entries efficiently.
Transformation and Validation: Converts data to required formats, verifying its accuracy.

What benefits and ROI can users expect from Oracle Enterprise Data Quality?

Data Integrity: Maintains consistent data accuracy.
Reduced Redundancy: Minimizes duplicate data across systems.
Enhanced Data Governance: Strengthens data management strategies.
Improved Accuracy: Boosts the precision of data validation.
Efficient Data Processing: Accelerates data handling routines.

Industries like education find Oracle Enterprise Data Quality invaluable for systems such as university fundraising, where tracking donor contributions accurately is crucial. Used in data governance, it manages quality during ETVL processes ensuring high precision for data warehouses and Data Lakehouses.

Oracle

SAP BusinessObjects Data Quality Management, version for SAP solutions (DQM for SAP), enables you to embed support for data quality directly into SAP ERP,CRM and MDG applications. Start by entering a new customer, supplier, or partner record using the SAP ERP, SAP CRM , SAP MDG applications. Then this version of SAP BusinessObjects Data Quality Management software corrects components of the address, validates the address based on referential data sources, and formats the address according to the norms of the applicable country. This solution helps in avoiding the duplicate entities entering into your SAP ERP, CRM and MDG applications(supports different MDG data models for address validation and duplicate checks) and also helps in searching and improving your existing data.

SAP

Sample Customers

Roka Bioscience, Statistics Centre _ Abu Dhabi , Raymond James Financial inc., CaixaBank, Industrial Bank of Korea, Posco, NHS Business Services Authority, RWE Power, LIFE Financial Group,

AOK Bundesverband, Surgutneftegas Open Joint Stock Company, Molson Coors Brewing Company, City of Buenos Aires, ASR Group, Citrix, EarlySense, Usha International Limited, Automotive Resources International, Wªrth Group, Takisada-Osaka Co. Ltd., Coelba, R

Buyer's Guide

Oracle Enterprise Data Quality (EDQ) vs. SAP Data Quality Management

December 2025

Free Report: Oracle Enterprise Data Quality (EDQ) vs. SAP Data Quality Management

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